Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach

Sci Rep. 2023 Aug 21;13(1):13637. doi: 10.1038/s41598-023-40953-5.

Abstract

Colorectal cancer (CRC) is the third most frequent cancer to be diagnosed in both females and males necessitating identification of effective biomarkers. An in-silico system biology approach called weighted gene co-expression network analysis (WGCNA) can be used to examine gene expression in a complicated network of regulatory genes. In the current study, the co-expression network of DEGs connected to CRC and their target genes was built using the WGCNA algorithm. GO and KEGG pathway analysis were carried out to learn more about the biological role of the DEmRNAs. These findings revealed that the genes were mostly enriched in the biological processes that were involved in the regulation of hormone levels, extracellular matrix organization, and extracellular structure organization. The intersection of genes between hub genes and DEmRNAs showed that DKC1, PA2G4, LYAR and NOLC1 were the clinically final hub genes of CRC.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adaptor Proteins, Signal Transducing
  • Algorithms
  • Biology*
  • Cell Cycle Proteins
  • Colorectal Neoplasms* / diagnosis
  • Colorectal Neoplasms* / genetics
  • DNA-Binding Proteins
  • Female
  • Gene Expression Profiling
  • Genes, Regulator
  • Humans
  • Male
  • Nuclear Proteins
  • RNA-Binding Proteins

Substances

  • DKC1 protein, human
  • Nuclear Proteins
  • Cell Cycle Proteins
  • PA2G4 protein, human
  • RNA-Binding Proteins
  • Adaptor Proteins, Signal Transducing
  • LYAR protein, human
  • DNA-Binding Proteins